Differential Privacy papers, 2023–2026

Key findings

• Differential Privacy fell from 117 papers in 2023 to 103 in 2026, so interest is cooling.
• NeurIPS publishes the most Differential Privacy work: 217 papers from 2023 to 2026, 45% of the four-venue total.
• The fastest-growing overlap is with Social aspects · accountability transparency and interpretability: papers tagged with both rose from 0 in 2023 to 22 in 2026.
• Among the 5 topics under Federated and Privacy, it ranks #3 by 2026 paper count; the fastest grower in the group, Secure Aggregation, is up 1.8x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Unified Framework for Adversary-Aware Differential Privacy Bounds
• ICML 2026Optimal conversion from Rényi Differential Privacy to $f$-Differential Privacy
• ICLR 2026Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
• CVPR 2026Fully Decentralized Certified Unlearning
• NeurIPS 2025Continual Release Moment Estimation with Differential Privacy
• ICML 2025Leveraging Per-Instance Privacy for Machine Unlearning
• ICLR 2025Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
• CVPR 2025Focal Split: Untethered Snapshot Depth from Differential Defocus
• NeurIPS 2024$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning
• ICML 2024Delving into Differentially Private Transformer
• ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
• CVPR 2024Affine Equivariant Networks Based on Differential Invariants
• NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
• ICML 2023Bayesian Estimation of Differential Privacy
• ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
• CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
• NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
• ICML 2026Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks
• ICLR 2026Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
• CVPR 2026LDP-Slicing Local Differential Privacy for Images via Randomized Bit-Plane Slicing

All Differential Privacy papers

117 papers, page 1 of 3

1. CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
2. CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
3. ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
4. ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
5. ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
6. ICLR 2023Characteristic Neural Ordinary Differential Equation
7. ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
8. ICLR 2023Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
9. ICLR 2023Differentially Private Adaptive Optimization with Delayed Preconditioners
10. ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
11. ICLR 2023Distributed Differential Privacy in Multi-Armed Bandits
12. ICLR 2023Easy Differentially Private Linear Regression
13. ICLR 2023Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
14. ICLR 2023Improved Convergence of Differential Private SGD with Gradient Clipping
15. ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
16. ICLR 2023Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks
17. ICLR 2023Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses
18. ICLR 2023Regression with Label Differential Privacy
19. ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
20. ICLR 2023Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
21. ICLR 2023Stochastic Differentially Private and Fair Learning
22. ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
23. ICLR 2023Transformer Meets Boundary Value Inverse Problems
24. ICML 2023A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
25. ICML 2023Algorithms for bounding contribution for histogram estimation under user-level privacy
26. ICML 2023Bayesian Estimation of Differential Privacy
27. ICML 2023Concurrent Shuffle Differential Privacy Under Continual Observation
28. ICML 2023Controlled Differential Equations on Long Sequences via Non-standard Wavelets
29. ICML 2023DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
30. ICML 2023Differential Privacy has Bounded Impact on Fairness in Classification
31. ICML 2023Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models
32. ICML 2023Differentially Private Sharpness-Aware Training
33. ICML 2023Effectively Using Public Data in Privacy Preserving Machine Learning
34. ICML 2023Federated Linear Contextual Bandits with User-level Differential Privacy
35. ICML 2023Fully-Adaptive Composition in Differential Privacy
36. ICML 2023Group Equivariant Fourier Neural Operators for Partial Differential Equations
37. ICML 2023Image Restoration with Mean-Reverting Stochastic Differential Equations
38. ICML 2023Label differential privacy and private training data release
39. ICML 2023Locally Regularized Neural Differential Equations: Some Black Boxes were meant to remain closed!
40. ICML 2023Multi-Task Differential Privacy Under Distribution Skew
41. ICML 2023Neural Stochastic Differential Games for Time-series Analysis
42. ICML 2023Online Local Differential Private Quantile Inference via Self-normalization
43. ICML 2023Predicting Ordinary Differential Equations with Transformers
44. ICML 2023Private Statistical Estimation of Many Quantiles
45. ICML 2023Random Grid Neural Processes for Parametric Partial Differential Equations
46. ICML 2023Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance
47. ICML 2023Statistical Indistinguishability of Learning Algorithms
48. ICML 2023Streaming Submodular Maximization with Differential Privacy
49. ICML 2023The Price of Differential Privacy under Continual Observation
50. ICML 2023The Saddle-Point Method in Differential Privacy

FAQ

How many Differential Privacy papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

479 in total: 117 in 2023, 113 in 2024, 146 in 2025, 103 in 2026.

How many Differential Privacy papers are at NeurIPS 2026?

NeurIPS 2026 has 23 Differential Privacy papers, versus 66 the year before.

How many Differential Privacy papers are at ICLR 2026?

ICLR 2026 has 31 Differential Privacy papers, versus 29 the year before.

How many Differential Privacy papers are at ICML 2026?

ICML 2026 has 42 Differential Privacy papers, versus 47 the year before.

How many Differential Privacy papers are at CVPR 2026?

CVPR 2026 has 7 Differential Privacy papers, versus 4 the year before.

Which conference publishes the most Differential Privacy papers?

NeurIPS, with 217 papers from 2023 to 2026.